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Record W1733916393 · doi:10.1126/science.aaa4019

Sea-level rise due to polar ice-sheet mass loss during past warm periods

2015· review· en· W1733916393 on OpenAlexaff
Andrea Dutton, Anders E. Carlson, Antony J. Long, Glenn A. Milne, Peter U. Clark, Robert M. DeConto, Benjamin P. Horton, Stefan Rahmstorf, Maureen E. Raymo

Bibliographic record

VenueScience · 2015
Typereview
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Ottawa
FundersNatural Environment Research CouncilSight Research UKNational Science Foundation
KeywordsIce sheetSea levelGreenland ice sheetGeologyPolarClimate changeClimatologyPost-glacial reboundGlacial periodFuture sea levelIce-sheet modelOceanographyAntarctic ice sheetSea iceCryosphereEnvironmental scienceAntarctic sea icePaleontology

Abstract

fetched live from OpenAlex

Interdisciplinary studies of geologic archives have ushered in a new era of deciphering magnitudes, rates, and sources of sea-level rise from polar ice-sheet loss during past warm periods. Accounting for glacial isostatic processes helps to reconcile spatial variability in peak sea level during marine isotope stages 5e and 11, when the global mean reached 6 to 9 meters and 6 to 13 meters higher than present, respectively. Dynamic topography introduces large uncertainties on longer time scales, precluding robust sea-level estimates for intervals such as the Pliocene. Present climate is warming to a level associated with significant polar ice-sheet loss in the past. Here, we outline advances and challenges involved in constraining ice-sheet sensitivity to climate change with use of paleo-sea level records.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.078
GPT teacher head0.334
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations891
Published2015
Admission routes1
Has abstractyes

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